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update: Add examples.
Browse files- .gitattributes +1 -0
- app.py +20 -17
- examples/ZFLFDfovqls_001310_001320.mp4 +3 -0
- examples/Zv7GyH-fpEY_2023.0_2033.0.mp4 +3 -0
.gitattributes
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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app.py
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import os
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import tempfile
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import gradio as gr
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import tensorflow as tf
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from moviepy.editor import VideoFileClip
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from ultralytics import YOLO
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from core.model import load_classifier
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from core.inference import FrameProcessor
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print("Tensorflow version " + tf.__version__)
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id_to_name = {
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0: 'Flying',
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1: 'Landing',
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2: 'Other',
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3: 'Straight Taxiing',
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4: 'Takeoff',
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5: 'Turning Maneuver',
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}
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print('Load classifier.')
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classifier_path = 'weights/classifier-7.keras'
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classifier = load_classifier(classifier_path)
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def fn(video: gr.Video):
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print('Process video.')
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return output
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inputs = gr.Video(sources=['upload'], label='Input Video')
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outputs = gr.Video(interactive=False, label='Aeroplane Position and Action Marked')
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iface = gr.Interface(
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fn=fn,
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inputs=inputs,
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outputs=outputs,
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)
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iface.launch()
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import gradio as gr
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import tensorflow as tf
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from moviepy.editor import VideoFileClip
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from ultralytics import YOLO
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from core.data import ClassMapping
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from core.model import load_classifier
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from core.inference import FrameProcessor
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print("Tensorflow version " + tf.__version__)
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print('Load classifier.')
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classifier_path = 'weights/classifier-7.keras'
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classifier = load_classifier(classifier_path)
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def fn(video: gr.Video):
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print('Process video.')
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output = f'Marked-{str(video)}'
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clip = VideoFileClip(video)
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id_to_name = {
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0: 'Flying',
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1: 'Landing',
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2: 'Other',
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3: 'Straight Taxiing',
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4: 'Takeoff',
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5: 'Turning Maneuver',
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}
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process_frame = FrameProcessor(detector, classifier, id_to_name)
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clip = clip.fl_image(process_frame)
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clip.write_videofile(output, fps=clip.fps, audio_codec='aac', logger=None)
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return output
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inputs = gr.Video(sources=['upload'], label='Input Video')
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outputs = gr.Video(interactive=False, label='Aeroplane Position and Action Marked')
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examples = [
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['examples/ZFLFDfovqls_001310_001320.mp4'] # cspell: disable-line
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['examples/Zv7GyH-fpEY_2023.0_2033.0.mp4']
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]
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iface = gr.Interface(
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fn=fn,
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inputs=inputs,
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outputs=outputs,
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examples=examples,
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)
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iface.launch()
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examples/ZFLFDfovqls_001310_001320.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:1cf18a000dac495924649008dfe29a413657e2cbd9c39400f4980867de39dba4
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size 669598
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examples/Zv7GyH-fpEY_2023.0_2033.0.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:dec949ee31a5e3b95f0b12a67c2abdcaf8d2e4fdab6dcae81d9cf563f77851a1
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size 1055493
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